Open-source CLI and agent skill that turns code, docs, PDFs and media into a queryable local knowledge graph.
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Graphify is a library and CLI from Graphify Labs that builds a knowledge graph of a project. It is invoked with /graphify inside an AI coding assistant, such as Claude Code, Cursor, Codex, Gemini CLI or GitHub Copilot. It maps code, docs, PDFs, images and video/audio into one graph that can be queried instead of grepping through files.
Code is parsed locally with tree-sitter AST across about 40 languages. This step is deterministic and uses no LLM. Docs, PDFs, images and video use the assistant's model or a configured API key for a semantic pass. Every edge is tagged EXTRACTED (explicit in source) or INFERRED (resolved by Graphify). The graph is not a vector index: it uses no embeddings and instead supports traversal through graphify query, graphify path and graphify explain. It also detects communities with the Leiden algorithm and surfaces highly connected "god nodes".
A run writes graph.html (interactive viewer), GRAPH_REPORT.md (key concepts and suggested questions) and graph.json (the full graph). Install requires Python 3.10+ and uv or pipx (uv tool install graphifyy, then graphify install). The README reports benchmark results on LOCOMO, LongMemEval-S and ERPNext, which are vendor-run figures. A separate hosted product, Graphify Cloud, adds always-on graphs, cross-repo support, formal verification and Sentry/Jira connectors. Its pricing is not detailed in the provided material beyond a free start with no card required.
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Turns codebases, docs and notes into a queryable knowledge graph that agents use as a memory layer, saving tokens. The creator ran it on his second brain and Future Tools codebase, viewed the graph, and queried it for themes and video ideas.
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